In [1]:
!pip install scikit-optimize
Requirement already satisfied: scikit-optimize in /opt/anaconda3/lib/python3.12/site-packages (0.10.2) Requirement already satisfied: joblib>=0.11 in /opt/anaconda3/lib/python3.12/site-packages (from scikit-optimize) (1.4.2) Requirement already satisfied: pyaml>=16.9 in /opt/anaconda3/lib/python3.12/site-packages (from scikit-optimize) (25.1.0) Requirement already satisfied: numpy>=1.20.3 in /opt/anaconda3/lib/python3.12/site-packages (from scikit-optimize) (1.26.4) Requirement already satisfied: scipy>=1.1.0 in /opt/anaconda3/lib/python3.12/site-packages (from scikit-optimize) (1.13.1) Requirement already satisfied: scikit-learn>=1.0.0 in /opt/anaconda3/lib/python3.12/site-packages (from scikit-optimize) (1.5.1) Requirement already satisfied: packaging>=21.3 in /opt/anaconda3/lib/python3.12/site-packages (from scikit-optimize) (24.1) Requirement already satisfied: PyYAML in /opt/anaconda3/lib/python3.12/site-packages (from pyaml>=16.9->scikit-optimize) (6.0.1) Requirement already satisfied: threadpoolctl>=3.1.0 in /opt/anaconda3/lib/python3.12/site-packages (from scikit-learn>=1.0.0->scikit-optimize) (3.5.0)
In [3]:
import pandas as pd
file_path = '/Users/fizza/path/to/data_ML_FZA.csv'
data = pd.read_csv(file_path)
def clean_target(value):
if value in ['xx', 'xx', 'xx']:
return 0.01
try:
return float(value)
except ValueError:
return None
data['y1'] = data['y1'].apply(clean_target)
data = data.dropna(subset=['y1'])
data['y1'] = data['y1'].astype(float)
data.info(), data['y1'].describe()
<class 'pandas.core.frame.DataFrame'> RangeIndex: 267 entries, 0 to 266 Data columns (total 67 columns): # Column Non-Null Count Dtype --- ------ -------------- ----- 0 y1 267 non-null float64 1 New a-ratio (%) 267 non-null int64 2 Unnamed: 25 0 non-null float64 3 x1_STol 267 non-null bool 4 x2_a 267 non-null bool 5 x2_b 267 non-null bool 6 x3_H 267 non-null bool 7 x3_N3 267 non-null bool 8 x3_OBn 267 non-null bool 9 x4_equatorial 267 non-null bool 10 x5_OBn 267 non-null bool 11 x6_OBn 267 non-null bool 12 x7_axial 267 non-null bool 13 x7_equatorial 267 non-null bool 14 x8_CH3 267 non-null bool 15 x8_OBn 267 non-null bool 16 x9_270 267 non-null bool 17 x9_2656 267 non-null bool 18 x9_17000 267 non-null bool 19 x9_72000 267 non-null bool 20 x9_1000000 267 non-null bool 21 x10_- 267 non-null bool 22 x10_OMe 267 non-null bool 23 x11_- 267 non-null bool 24 x11_a 267 non-null bool 25 x12_- 267 non-null bool 26 x12_OBn 267 non-null bool 27 x13_- 267 non-null bool 28 x13_OBn 267 non-null bool 29 x14_- 267 non-null bool 30 x14_OBn 267 non-null bool 31 x14_OH 267 non-null bool 32 x15_- 267 non-null bool 33 x15_OBn 267 non-null bool 34 x15_OH 267 non-null bool 35 x16_1_OH 267 non-null bool 36 x16_4_OH 267 non-null bool 37 x16_6_OH 267 non-null bool 38 x17_Secondary 267 non-null bool 39 x17_primary 267 non-null bool 40 x17_secondary 267 non-null bool 41 x17_tertiary 267 non-null bool 42 x18_1.0 267 non-null bool 43 x18_1.36 267 non-null bool 44 x18_3.51 267 non-null bool 45 x18_7.16 267 non-null bool 46 x18_80.0 267 non-null bool 47 x18_100.0 267 non-null bool 48 x19_-20 ℃ 267 non-null bool 49 x19_-40 ℃ 267 non-null bool 50 x19_0 ℃ 267 non-null bool 51 x19_25 ℃ 267 non-null bool 52 x20_DCM 267 non-null bool 53 x20_DCM/ACN 267 non-null bool 54 x20_DCM/DMF 267 non-null bool 55 x20_DCM/p-Dioxane 267 non-null bool 56 x20_THF 267 non-null bool 57 x20_Toluene 267 non-null bool 58 x21_0.018M 267 non-null bool 59 x21_0.036M 267 non-null bool 60 x21_0.051M 267 non-null bool 61 x21_0.167M 267 non-null bool 62 x21_0.308M 267 non-null bool 63 x22_1:0.66 267 non-null bool 64 x22_1:1.5 267 non-null bool 65 x23_IDCP 267 non-null bool 66 x23_NIS_TfOH 267 non-null bool dtypes: bool(64), float64(2), int64(1) memory usage: 23.1 KB
Out[3]:
(None, count 267.000000 mean 51.592547 std 31.597137 min 0.000000 25% 27.000000 50% 55.000000 75% 75.000000 max 100.000000 Name: y1, dtype: float64)
In [5]:
import pandas as pd
import numpy as np
from sklearn.model_selection import train_test_split
from sklearn.ensemble import RandomForestRegressor
import matplotlib.pyplot as plt
from IPython.display import display, HTML
file_path = '/Users/fizza/path/to/data_ML_FZA.csv'
data = pd.read_csv(file_path)
def clean_target(value):
if value in ['xx', 'xx', 'xx']:
return 0.01
try:
return float(value)
except ValueError:
return None
data['y1'] = data['y1'].apply(clean_target)
data = data.dropna(subset=['y1'])
data['y1'] = data['y1'].astype(float)
X = data.drop(columns=['y1'])
y = data['y1']
X_train, X_test, y_train, y_test = train_test_split(X, y, test_size=0.1, random_state=42)
model = RandomForestRegressor(random_state=42)
model.fit(X_train, y_train)
new_data_path = '/Users/fizza/path/to/data_ML_FZA.cs/vencoded_data_ML_FZA.csv'
new_data = pd.read_csv(new_data_path)
if 'y1' in new_data.columns:
new_data['y1'] = new_data['y1'].apply(clean_target)
new_data_encoded = pd.get_dummies(new_data)
missing_cols = set(X.columns) - set(new_data_encoded.columns)
for col in missing_cols:
new_data_encoded[col] = 0
new_data_encoded = new_data_encoded[X.columns]
new_pred_a_ratio = model.predict(new_data_encoded)
new_data['New a-ratio'] = new_pred_a_ratio
output_csv_path = '/Users/fizza/path/to/Predicted_alpha_ratios-FZA.csv'
new_data.to_csv(output_csv_path, index=False)
display(new_data.head())
html_link = f'<a href="file:///{output_csv_path}" download>Download the new alpha ratios CSV file</a>'
plt.figure(figsize=(10, 6))
plt.hist(new_data['New a-ratio'], bins=20, color='skyblue', edgecolor='black')
plt.xlabel('New a-ratio values')
plt.ylabel('Frequency')
plt.title('Distribution of Predicted New Alpha Ratios')
plt.show()
| y1 | New a-ratio (%) | Unnamed: 25 | x1_STol | x2_a | x2_b | x3_H | x3_N3 | x3_OBn | x4_equatorial | ... | x21_0.018M | x21_0.036M | x21_0.051M | x21_0.167M | x21_0.308M | x22_1:0.66 | x22_1:1.5 | x23_IDCP | x23_NIS_TfOH | New a-ratio | |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 0 | 0.0 | 0 | NaN | True | False | True | False | True | False | True | ... | False | False | False | True | False | False | True | False | True | 0.0005 |
| 1 | 0.0 | 9 | NaN | True | False | True | False | False | True | True | ... | False | False | False | True | False | False | True | False | True | 2.0209 |
| 2 | 62.0 | 52 | NaN | True | False | True | False | False | True | True | ... | False | False | False | True | False | False | True | False | True | 58.1100 |
| 3 | 83.0 | 70 | NaN | True | False | True | False | False | True | True | ... | False | False | False | True | False | False | True | False | True | 79.1400 |
| 4 | 40.0 | 37 | NaN | True | True | False | True | False | False | True | ... | False | False | False | True | False | False | True | False | True | 38.8200 |
5 rows × 68 columns
In [8]:
import pandas as pd
import numpy as np
from sklearn.ensemble import RandomForestRegressor
from sklearn.model_selection import train_test_split, GridSearchCV
from sklearn.metrics import mean_squared_error, r2_score
import matplotlib.pyplot as plt
from scipy.stats import linregress
def clean_target(value):
if value in ['No Reaction', 'Trace', 'Later']:
return np.nan
try:
return float(value)
except ValueError:
return np.nan
data = pd.read_csv('/Users/fizza/path/to/predicted_alpha_ratios.csv')
data['y1'] = data['y1'].apply(clean_target)
data = data.dropna(subset=['y1'])
data = data.apply(pd.to_numeric, errors='coerce')
data.fillna(data.mean(), inplace=True)
X = data.drop(columns=['y1'])
y = data['y1']
X_train, X_test, y_train, y_test = train_test_split(
X, y,
test_size=0.3,
random_state=42
)
param_grid = {
'n_estimators': [100, 200, 500],
'max_depth': [10, 20, None],
'min_samples_split': [2, 5, 10],
'min_samples_leaf': [1, 2, 4]
}
grid_search = GridSearchCV(
RandomForestRegressor(random_state=42),
param_grid,
cv=5,
scoring='neg_mean_squared_error',
verbose=2,
n_jobs=-1
)
grid_search.fit(X_train, y_train)
best_model = grid_search.best_estimator_
print("Best Parameters:", grid_search.best_params_)
y_train_pred = best_model.predict(X_train)
y_test_pred = best_model.predict(X_test)
all_actual = np.concatenate([y_train, y_test])
all_predicted = np.concatenate([y_train_pred, y_test_pred])
r2 = r2_score(all_actual, all_predicted)
mse = mean_squared_error(all_actual, all_predicted)
rmse = np.sqrt(mse)
print(f"R²: {r2:.3f}")
print(f"RMSE: {rmse:.3f}")
slope, intercept, r_value, _, _ = linregress(all_actual, all_predicted)
plt.figure(figsize=(4, 3), dpi=800)
plt.scatter(all_actual, all_predicted, alpha=0.7, color='green', label='Data points')
plt.plot(
[all_actual.min(), all_actual.max()],
[all_actual.min(), all_actual.max()],
color='gray', linestyle='--', label='Perfect prediction'
)
metrics_text = (
f"$R^2$: {r2:.3f}\n"
f"RMSE: {rmse:.3f}\n"
f"Slope: {slope:.3f}\n"
f"Pearson r: {r_value:.3f}"
)
plt.gca().text(
0.96, 0.05, metrics_text, transform=plt.gca().transAxes, fontsize=8,
verticalalignment='bottom', horizontalalignment='right',
bbox=dict(boxstyle='round,pad=0.5', edgecolor='black', facecolor='white')
)
plt.xlabel('Actual α-ratio (%)', fontsize=10)
plt.ylabel('Predicted α-ratio (%)', fontsize=10)
plt.tight_layout()
plt.show()
Fitting 5 folds for each of 81 candidates, totalling 405 fits
Best Parameters: {'max_depth': 10, 'min_samples_leaf': 2, 'min_samples_split': 5, 'n_estimators': 500}
R²: 0.936
RMSE: 7.977
In [9]:
from sklearn.metrics import r2_score, mean_squared_error
import matplotlib.pyplot as plt
from scipy.stats import linregress
import numpy as np
r2_train = r2_score(y_train, y_train_pred)
r2_test = r2_score(y_test, y_test_pred)
rmse_train = np.sqrt(mean_squared_error(y_train, y_train_pred))
rmse_test = np.sqrt(mean_squared_error(y_test, y_test_pred))
sns.set(style="whitegrid", font_scale=1.2)
plt.figure(figsize=(5, 4), dpi=600)
plt.scatter(y_train, y_train_pred, c='#1f77b4', edgecolor='k', alpha=0.6, label=f'Training (R² = {r2_train:.2f})')
plt.scatter(y_test, y_test_pred, c='#d62728', edgecolor='k', alpha=0.6, label=f'Testing (R² = {r2_test:.2f})')
min_val = min(y_train.min(), y_test.min())
max_val = max(y_train.max(), y_test.max())
plt.plot([min_val, max_val], [min_val, max_val], linestyle='--', color='gray', label='Perfect prediction')
plt.legend(frameon=True, fontsize=10, loc='lower right')
plt.xlabel('Actual α-ratio (%)')
plt.ylabel('Predicted α-ratio (%)')
plt.title('Actual vs Predicted α-ratio')
plt.tight_layout()
plt.show()
In [3]:
import pandas as pd
import numpy as np
import joblib
import matplotlib.pyplot as plt
import seaborn as sns
from sklearn.metrics import r2_score, mean_squared_error
from scipy.stats import pearsonr
font_size = 15
xlim = (0, 100)
ylim = (0, 100)
max_points = 800
file_path = '/Users/fizza/path/to/Gly-data a_ratio2.csv'
df = pd.read_csv(file_path)
target_col = 'y1'
base_a_ratio_series = pd.to_numeric(df[target_col], errors='coerce')
df = df.loc[base_a_ratio_series.dropna().index]
base_a_ratio = base_a_ratio_series.dropna().values
feature_cols = df.columns.drop(target_col)
X = df[feature_cols]
rf_model = joblib.load('/Users/fizza/path/to/random_forest_model.pkl')
xgb_model = joblib.load('/Users/fizza/path/to/xgboost_model.pkl')
ridge_model = joblib.load('/Users/fizza/path/to/ridge_model.pkl')
lasso_model = joblib.load('/Users/fizza/path/to/lasso_model.pkl')
catboost_model = joblib.load('/Users/fizza/path/to/catboost_model.pkl')
gb_model = joblib.load('/Users/fizza/path/to/gradient_boosting_model.pkl')
svr_model = joblib.load('/Users/fizza/path/to/svr_model.pkl')
dt_model = joblib.load('/Users/fizza/path/to/decision_tree_model.pkl')
ada_model = joblib.load('/Users/fizza/path/to/adaboost_model.pkl')
rf_pred_a_ratio = rf_model.predict(X)
xgb_pred_a_ratio = xgb_model.predict(X)
ridge_pred_a_ratio = ridge_model.predict(X)
lasso_pred_a_ratio = lasso_model.predict(X)
catboost_pred_a_ratio = catboost_model.predict(X)
gb_pred_a_ratio = gb_model.predict(X)
svr_pred_a_ratio = svr_model.predict(X)
dt_pred_a_ratio = dt_model.predict(X)
ada_pred_a_ratio = ada_model.predict(X)
best_w = 0.7
best_hybrid = best_w * rf_pred_a_ratio + (1 - best_w) * xgb_pred_a_ratio
predictions_a_ratio = {
'Hybrid Model': best_hybrid,
'Random Forest': rf_pred_a_ratio,
'XGBoost': xgb_pred_a_ratio,
'CatBoost': catboost_pred_a_ratio,
'Gradient Boosting': gb_pred_a_ratio,
'Ridge Regression': ridge_pred_a_ratio,
'Lasso Regression': lasso_pred_a_ratio,
'Support Vector Regressor': svr_pred_a_ratio,
'Decision Tree': dt_pred_a_ratio,
'AdaBoost': ada_pred_a_ratio,
}
df_a_ratio = pd.DataFrame({'Actual': base_a_ratio, **predictions_a_ratio})
r2_scores = {model: r2_score(df_a_ratio['Actual'], df_a_ratio[model]) for model in predictions_a_ratio}
sorted_models = sorted(predictions_a_ratio.keys(), key=lambda m: r2_scores[m], reverse=True)
colors = sns.color_palette("husl", len(sorted_models))
fig, axes = plt.subplots(2, 5, figsize=(23, 7), dpi=800)
axes = axes.flatten()
for ax, model, color in zip(axes, sorted_models, colors):
r2 = r2_scores[model]
n_points = min(max_points, int((r2 ** 2) * max_points), len(df_a_ratio))
sub_df = df_a_ratio[['Actual', model]].sample(n=n_points, random_state=42)
pred = sub_df[model]
actual = sub_df['Actual']
rmse = mean_squared_error(actual, pred, squared=False)
r, _ = pearsonr(actual, pred)
sns.regplot(
x=actual, y=pred, ax=ax,
scatter_kws={'alpha': 0.7, 'color': color, 's': 25, 'edgecolor': 'black', 'linewidths': 0.3},
line_kws={'color': 'black', 'linestyle': '--'}, truncate=False
)
ax.plot(xlim, ylim, 'k--', lw=0.8)
ax.set_xlim(*xlim)
ax.set_ylim(*ylim)
ax.set_title(f"{model}", fontsize=font_size + 2, fontweight='bold')
ax.tick_params(labelsize=font_size - 0.01)
ax.set_xlabel("")
ax.set_ylabel("")
if model == "Hybrid Model":
ax.text(
0.95, 0.05,
f"$\\bf{{R^2 = {r2:.2f}}}$\\n$\\bf{{RMSE = {rmse:.2f}}}$\\n$\\bf{{Pearson\\'s\\ r = {r:.2f}}}$",
transform=ax.transAxes,
fontsize=font_size - 0.5,
verticalalignment='bottom',
horizontalalignment='right',
bbox=dict(boxstyle="round", facecolor="white", edgecolor='gray', alpha=0.85),
fontweight='bold',
fontname='Arial'
)
else:
ax.text(
0.95, 0.05,
f"$R^2$ = {r2:.2f}\\nRMSE = {rmse:.2f}\\nPearson's r = {r:.2f}",
transform=ax.transAxes,
fontsize=font_size - 0.5,
verticalalignment='bottom',
horizontalalignment='right',
bbox=dict(boxstyle="round", facecolor="white", edgecolor='gray', alpha=0.85)
)
fig.text(0.525, 0.01, "Observed a-Ratio (%)", ha='center', fontsize=font_size + 8, fontweight='bold')
fig.text(0.04, 0.55, "Predicted a-Ratio (%)", va='center', rotation='vertical', fontsize=font_size + 8, fontweight='bold')
plt.subplots_adjust(left=0.08, bottom=0.10, right=0.97, top=0.94, wspace=0.16, hspace=0.27)
plt.savefig("path/to/a_ratio_scatter.png", dpi=800)
plt.show()
/opt/anaconda3/lib/python3.12/site-packages/sklearn/metrics/_regression.py:492: FutureWarning: 'squared' is deprecated in version 1.4 and will be removed in 1.6. To calculate the root mean squared error, use the function'root_mean_squared_error'. warnings.warn( /opt/anaconda3/lib/python3.12/site-packages/sklearn/metrics/_regression.py:492: FutureWarning: 'squared' is deprecated in version 1.4 and will be removed in 1.6. To calculate the root mean squared error, use the function'root_mean_squared_error'. warnings.warn( /opt/anaconda3/lib/python3.12/site-packages/sklearn/metrics/_regression.py:492: FutureWarning: 'squared' is deprecated in version 1.4 and will be removed in 1.6. To calculate the root mean squared error, use the function'root_mean_squared_error'. warnings.warn( /opt/anaconda3/lib/python3.12/site-packages/sklearn/metrics/_regression.py:492: FutureWarning: 'squared' is deprecated in version 1.4 and will be removed in 1.6. To calculate the root mean squared error, use the function'root_mean_squared_error'. warnings.warn( /opt/anaconda3/lib/python3.12/site-packages/sklearn/metrics/_regression.py:492: FutureWarning: 'squared' is deprecated in version 1.4 and will be removed in 1.6. To calculate the root mean squared error, use the function'root_mean_squared_error'. warnings.warn( /opt/anaconda3/lib/python3.12/site-packages/sklearn/metrics/_regression.py:492: FutureWarning: 'squared' is deprecated in version 1.4 and will be removed in 1.6. To calculate the root mean squared error, use the function'root_mean_squared_error'. warnings.warn( /opt/anaconda3/lib/python3.12/site-packages/sklearn/metrics/_regression.py:492: FutureWarning: 'squared' is deprecated in version 1.4 and will be removed in 1.6. To calculate the root mean squared error, use the function'root_mean_squared_error'. warnings.warn( /opt/anaconda3/lib/python3.12/site-packages/sklearn/metrics/_regression.py:492: FutureWarning: 'squared' is deprecated in version 1.4 and will be removed in 1.6. To calculate the root mean squared error, use the function'root_mean_squared_error'. warnings.warn( /opt/anaconda3/lib/python3.12/site-packages/sklearn/metrics/_regression.py:492: FutureWarning: 'squared' is deprecated in version 1.4 and will be removed in 1.6. To calculate the root mean squared error, use the function'root_mean_squared_error'. warnings.warn( /opt/anaconda3/lib/python3.12/site-packages/sklearn/metrics/_regression.py:492: FutureWarning: 'squared' is deprecated in version 1.4 and will be removed in 1.6. To calculate the root mean squared error, use the function'root_mean_squared_error'. warnings.warn( /opt/anaconda3/lib/python3.12/site-packages/sklearn/metrics/_regression.py:492: FutureWarning: 'squared' is deprecated in version 1.4 and will be removed in 1.6. To calculate the root mean squared error, use the function'root_mean_squared_error'. warnings.warn( /opt/anaconda3/lib/python3.12/site-packages/sklearn/metrics/_regression.py:492: FutureWarning: 'squared' is deprecated in version 1.4 and will be removed in 1.6. To calculate the root mean squared error, use the function'root_mean_squared_error'. warnings.warn( /opt/anaconda3/lib/python3.12/site-packages/sklearn/metrics/_regression.py:492: FutureWarning: 'squared' is deprecated in version 1.4 and will be removed in 1.6. To calculate the root mean squared error, use the function'root_mean_squared_error'. warnings.warn( /opt/anaconda3/lib/python3.12/site-packages/sklearn/metrics/_regression.py:492: FutureWarning: 'squared' is deprecated in version 1.4 and will be removed in 1.6. To calculate the root mean squared error, use the function'root_mean_squared_error'. warnings.warn( /opt/anaconda3/lib/python3.12/site-packages/sklearn/metrics/_regression.py:492: FutureWarning: 'squared' is deprecated in version 1.4 and will be removed in 1.6. To calculate the root mean squared error, use the function'root_mean_squared_error'. warnings.warn( /opt/anaconda3/lib/python3.12/site-packages/sklearn/metrics/_regression.py:492: FutureWarning: 'squared' is deprecated in version 1.4 and will be removed in 1.6. To calculate the root mean squared error, use the function'root_mean_squared_error'. warnings.warn( /opt/anaconda3/lib/python3.12/site-packages/sklearn/metrics/_regression.py:492: FutureWarning: 'squared' is deprecated in version 1.4 and will be removed in 1.6. To calculate the root mean squared error, use the function'root_mean_squared_error'. warnings.warn( /opt/anaconda3/lib/python3.12/site-packages/sklearn/metrics/_regression.py:492: FutureWarning: 'squared' is deprecated in version 1.4 and will be removed in 1.6. To calculate the root mean squared error, use the function'root_mean_squared_error'. warnings.warn( /opt/anaconda3/lib/python3.12/site-packages/sklearn/metrics/_regression.py:492: FutureWarning: 'squared' is deprecated in version 1.4 and will be removed in 1.6. To calculate the root mean squared error, use the function'root_mean_squared_error'. warnings.warn( /opt/anaconda3/lib/python3.12/site-packages/sklearn/metrics/_regression.py:492: FutureWarning: 'squared' is deprecated in version 1.4 and will be removed in 1.6. To calculate the root mean squared error, use the function'root_mean_squared_error'. warnings.warn( /opt/anaconda3/lib/python3.12/site-packages/sklearn/metrics/_regression.py:492: FutureWarning: 'squared' is deprecated in version 1.4 and will be removed in 1.6. To calculate the root mean squared error, use the function'root_mean_squared_error'. warnings.warn( /opt/anaconda3/lib/python3.12/site-packages/sklearn/metrics/_regression.py:492: FutureWarning: 'squared' is deprecated in version 1.4 and will be removed in 1.6. To calculate the root mean squared error, use the function'root_mean_squared_error'. warnings.warn( /opt/anaconda3/lib/python3.12/site-packages/sklearn/metrics/_regression.py:492: FutureWarning: 'squared' is deprecated in version 1.4 and will be removed in 1.6. To calculate the root mean squared error, use the function'root_mean_squared_error'. warnings.warn( /opt/anaconda3/lib/python3.12/site-packages/sklearn/metrics/_regression.py:492: FutureWarning: 'squared' is deprecated in version 1.4 and will be removed in 1.6. To calculate the root mean squared error, use the function'root_mean_squared_error'. warnings.warn( /opt/anaconda3/lib/python3.12/site-packages/sklearn/metrics/_regression.py:492: FutureWarning: 'squared' is deprecated in version 1.4 and will be removed in 1.6. To calculate the root mean squared error, use the function'root_mean_squared_error'. warnings.warn( /opt/anaconda3/lib/python3.12/site-packages/sklearn/metrics/_regression.py:492: FutureWarning: 'squared' is deprecated in version 1.4 and will be removed in 1.6. To calculate the root mean squared error, use the function'root_mean_squared_error'. warnings.warn( /opt/anaconda3/lib/python3.12/site-packages/sklearn/metrics/_regression.py:492: FutureWarning: 'squared' is deprecated in version 1.4 and will be removed in 1.6. To calculate the root mean squared error, use the function'root_mean_squared_error'. warnings.warn( /opt/anaconda3/lib/python3.12/site-packages/sklearn/metrics/_regression.py:492: FutureWarning: 'squared' is deprecated in version 1.4 and will be removed in 1.6. To calculate the root mean squared error, use the function'root_mean_squared_error'. warnings.warn( /opt/anaconda3/lib/python3.12/site-packages/sklearn/metrics/_regression.py:492: FutureWarning: 'squared' is deprecated in version 1.4 and will be removed in 1.6. To calculate the root mean squared error, use the function'root_mean_squared_error'. warnings.warn( /opt/anaconda3/lib/python3.12/site-packages/sklearn/metrics/_regression.py:492: FutureWarning: 'squared' is deprecated in version 1.4 and will be removed in 1.6. To calculate the root mean squared error, use the function'root_mean_squared_error'. warnings.warn( /opt/anaconda3/lib/python3.12/site-packages/sklearn/metrics/_regression.py:492: FutureWarning: 'squared' is deprecated in version 1.4 and will be removed in 1.6. To calculate the root mean squared error, use the function'root_mean_squared_error'. warnings.warn( /opt/anaconda3/lib/python3.12/site-packages/sklearn/metrics/_regression.py:492: FutureWarning: 'squared' is deprecated in version 1.4 and will be removed in 1.6. To calculate the root mean squared error, use the function'root_mean_squared_error'. warnings.warn( /opt/anaconda3/lib/python3.12/site-packages/sklearn/metrics/_regression.py:492: FutureWarning: 'squared' is deprecated in version 1.4 and will be removed in 1.6. To calculate the root mean squared error, use the function'root_mean_squared_error'. warnings.warn( /opt/anaconda3/lib/python3.12/site-packages/sklearn/metrics/_regression.py:492: FutureWarning: 'squared' is deprecated in version 1.4 and will be removed in 1.6. To calculate the root mean squared error, use the function'root_mean_squared_error'. warnings.warn( /opt/anaconda3/lib/python3.12/site-packages/sklearn/metrics/_regression.py:492: FutureWarning: 'squared' is deprecated in version 1.4 and will be removed in 1.6. To calculate the root mean squared error, use the function'root_mean_squared_error'. warnings.warn( /opt/anaconda3/lib/python3.12/site-packages/sklearn/metrics/_regression.py:492: FutureWarning: 'squared' is deprecated in version 1.4 and will be removed in 1.6. To calculate the root mean squared error, use the function'root_mean_squared_error'. warnings.warn( /opt/anaconda3/lib/python3.12/site-packages/sklearn/metrics/_regression.py:492: FutureWarning: 'squared' is deprecated in version 1.4 and will be removed in 1.6. To calculate the root mean squared error, use the function'root_mean_squared_error'. warnings.warn( /opt/anaconda3/lib/python3.12/site-packages/sklearn/metrics/_regression.py:492: FutureWarning: 'squared' is deprecated in version 1.4 and will be removed in 1.6. To calculate the root mean squared error, use the function'root_mean_squared_error'. warnings.warn( /opt/anaconda3/lib/python3.12/site-packages/sklearn/metrics/_regression.py:492: FutureWarning: 'squared' is deprecated in version 1.4 and will be removed in 1.6. To calculate the root mean squared error, use the function'root_mean_squared_error'. warnings.warn( /opt/anaconda3/lib/python3.12/site-packages/sklearn/metrics/_regression.py:492: FutureWarning: 'squared' is deprecated in version 1.4 and will be removed in 1.6. To calculate the root mean squared error, use the function'root_mean_squared_error'. warnings.warn( /opt/anaconda3/lib/python3.12/site-packages/sklearn/metrics/_regression.py:492: FutureWarning: 'squared' is deprecated in version 1.4 and will be removed in 1.6. To calculate the root mean squared error, use the function'root_mean_squared_error'. warnings.warn( /opt/anaconda3/lib/python3.12/site-packages/sklearn/metrics/_regression.py:492: FutureWarning: 'squared' is deprecated in version 1.4 and will be removed in 1.6. To calculate the root mean squared error, use the function'root_mean_squared_error'. warnings.warn( /opt/anaconda3/lib/python3.12/site-packages/sklearn/metrics/_regression.py:492: FutureWarning: 'squared' is deprecated in version 1.4 and will be removed in 1.6. To calculate the root mean squared error, use the function'root_mean_squared_error'. warnings.warn( /opt/anaconda3/lib/python3.12/site-packages/sklearn/metrics/_regression.py:492: FutureWarning: 'squared' is deprecated in version 1.4 and will be removed in 1.6. To calculate the root mean squared error, use the function'root_mean_squared_error'. warnings.warn( /opt/anaconda3/lib/python3.12/site-packages/sklearn/metrics/_regression.py:492: FutureWarning: 'squared' is deprecated in version 1.4 and will be removed in 1.6. To calculate the root mean squared error, use the function'root_mean_squared_error'. warnings.warn( /opt/anaconda3/lib/python3.12/site-packages/sklearn/metrics/_regression.py:492: FutureWarning: 'squared' is deprecated in version 1.4 and will be removed in 1.6. To calculate the root mean squared error, use the function'root_mean_squared_error'. warnings.warn( /opt/anaconda3/lib/python3.12/site-packages/sklearn/metrics/_regression.py:492: FutureWarning: 'squared' is deprecated in version 1.4 and will be removed in 1.6. To calculate the root mean squared error, use the function'root_mean_squared_error'. warnings.warn( /opt/anaconda3/lib/python3.12/site-packages/sklearn/metrics/_regression.py:492: FutureWarning: 'squared' is deprecated in version 1.4 and will be removed in 1.6. To calculate the root mean squared error, use the function'root_mean_squared_error'. warnings.warn( /opt/anaconda3/lib/python3.12/site-packages/sklearn/metrics/_regression.py:492: FutureWarning: 'squared' is deprecated in version 1.4 and will be removed in 1.6. To calculate the root mean squared error, use the function'root_mean_squared_error'. warnings.warn( /opt/anaconda3/lib/python3.12/site-packages/sklearn/metrics/_regression.py:492: FutureWarning: 'squared' is deprecated in version 1.4 and will be removed in 1.6. To calculate the root mean squared error, use the function'root_mean_squared_error'. warnings.warn( /opt/anaconda3/lib/python3.12/site-packages/sklearn/metrics/_regression.py:492: FutureWarning: 'squared' is deprecated in version 1.4 and will be removed in 1.6. To calculate the root mean squared error, use the function'root_mean_squared_error'. warnings.warn( /opt/anaconda3/lib/python3.12/site-packages/sklearn/metrics/_regression.py:492: FutureWarning: 'squared' is deprecated in version 1.4 and will be removed in 1.6. To calculate the root mean squared error, use the function'root_mean_squared_error'. warnings.warn( /opt/anaconda3/lib/python3.12/site-packages/sklearn/metrics/_regression.py:492: FutureWarning: 'squared' is deprecated in version 1.4 and will be removed in 1.6. To calculate the root mean squared error, use the function'root_mean_squared_error'. warnings.warn( /opt/anaconda3/lib/python3.12/site-packages/sklearn/metrics/_regression.py:492: FutureWarning: 'squared' is deprecated in version 1.4 and will be removed in 1.6. To calculate the root mean squared error, use the function'root_mean_squared_error'. warnings.warn( /opt/anaconda3/lib/python3.12/site-packages/sklearn/metrics/_regression.py:492: FutureWarning: 'squared' is deprecated in version 1.4 and will be removed in 1.6. To calculate the root mean squared error, use the function'root_mean_squared_error'. warnings.warn( /opt/anaconda3/lib/python3.12/site-packages/sklearn/metrics/_regression.py:492: FutureWarning: 'squared' is deprecated in version 1.4 and will be removed in 1.6. To calculate the root mean squared error, use the function'root_mean_squared_error'. warnings.warn( /opt/anaconda3/lib/python3.12/site-packages/sklearn/metrics/_regression.py:492: FutureWarning: 'squared' is deprecated in version 1.4 and will be removed in 1.6. To calculate the root mean squared error, use the function'root_mean_squared_error'. warnings.warn( /opt/anaconda3/lib/python3.12/site-packages/sklearn/metrics/_regression.py:492: FutureWarning: 'squared' is deprecated in version 1.4 and will be removed in 1.6. To calculate the root mean squared error, use the function'root_mean_squared_error'. warnings.warn( /opt/anaconda3/lib/python3.12/site-packages/sklearn/metrics/_regression.py:492: FutureWarning: 'squared' is deprecated in version 1.4 and will be removed in 1.6. To calculate the root mean squared error, use the function'root_mean_squared_error'. warnings.warn( /opt/anaconda3/lib/python3.12/site-packages/sklearn/metrics/_regression.py:492: FutureWarning: 'squared' is deprecated in version 1.4 and will be removed in 1.6. To calculate the root mean squared error, use the function'root_mean_squared_error'. warnings.warn( /opt/anaconda3/lib/python3.12/site-packages/sklearn/metrics/_regression.py:492: FutureWarning: 'squared' is deprecated in version 1.4 and will be removed in 1.6. To calculate the root mean squared error, use the function'root_mean_squared_error'. warnings.warn( /opt/anaconda3/lib/python3.12/site-packages/sklearn/metrics/_regression.py:492: FutureWarning: 'squared' is deprecated in version 1.4 and will be removed in 1.6. To calculate the root mean squared error, use the function'root_mean_squared_error'. warnings.warn( /opt/anaconda3/lib/python3.12/site-packages/sklearn/metrics/_regression.py:492: FutureWarning: 'squared' is deprecated in version 1.4 and will be removed in 1.6. To calculate the root mean squared error, use the function'root_mean_squared_error'. warnings.warn( /opt/anaconda3/lib/python3.12/site-packages/sklearn/metrics/_regression.py:492: FutureWarning: 'squared' is deprecated in version 1.4 and will be removed in 1.6. To calculate the root mean squared error, use the function'root_mean_squared_error'. warnings.warn( /opt/anaconda3/lib/python3.12/site-packages/sklearn/metrics/_regression.py:492: FutureWarning: 'squared' is deprecated in version 1.4 and will be removed in 1.6. To calculate the root mean squared error, use the function'root_mean_squared_error'. warnings.warn( /opt/anaconda3/lib/python3.12/site-packages/sklearn/metrics/_regression.py:492: FutureWarning: 'squared' is deprecated in version 1.4 and will be removed in 1.6. To calculate the root mean squared error, use the function'root_mean_squared_error'. warnings.warn( /opt/anaconda3/lib/python3.12/site-packages/sklearn/metrics/_regression.py:492: FutureWarning: 'squared' is deprecated in version 1.4 and will be removed in 1.6. To calculate the root mean squared error, use the function'root_mean_squared_error'. warnings.warn( /opt/anaconda3/lib/python3.12/site-packages/sklearn/metrics/_regression.py:492: FutureWarning: 'squared' is deprecated in version 1.4 and will be removed in 1.6. To calculate the root mean squared error, use the function'root_mean_squared_error'. warnings.warn( /opt/anaconda3/lib/python3.12/site-packages/sklearn/metrics/_regression.py:492: FutureWarning: 'squared' is deprecated in version 1.4 and will be removed in 1.6. To calculate the root mean squared error, use the function'root_mean_squared_error'. warnings.warn( /opt/anaconda3/lib/python3.12/site-packages/sklearn/metrics/_regression.py:492: FutureWarning: 'squared' is deprecated in version 1.4 and will be removed in 1.6. To calculate the root mean squared error, use the function'root_mean_squared_error'. warnings.warn( /opt/anaconda3/lib/python3.12/site-packages/sklearn/metrics/_regression.py:492: FutureWarning: 'squared' is deprecated in version 1.4 and will be removed in 1.6. To calculate the root mean squared error, use the function'root_mean_squared_error'. warnings.warn( /opt/anaconda3/lib/python3.12/site-packages/sklearn/metrics/_regression.py:492: FutureWarning: 'squared' is deprecated in version 1.4 and will be removed in 1.6. To calculate the root mean squared error, use the function'root_mean_squared_error'. warnings.warn( /opt/anaconda3/lib/python3.12/site-packages/sklearn/metrics/_regression.py:492: FutureWarning: 'squared' is deprecated in version 1.4 and will be removed in 1.6. To calculate the root mean squared error, use the function'root_mean_squared_error'. warnings.warn( /opt/anaconda3/lib/python3.12/site-packages/sklearn/metrics/_regression.py:492: FutureWarning: 'squared' is deprecated in version 1.4 and will be removed in 1.6. To calculate the root mean squared error, use the function'root_mean_squared_error'. warnings.warn( /opt/anaconda3/lib/python3.12/site-packages/sklearn/metrics/_regression.py:492: FutureWarning: 'squared' is deprecated in version 1.4 and will be removed in 1.6. To calculate the root mean squared error, use the function'root_mean_squared_error'. warnings.warn( /opt/anaconda3/lib/python3.12/site-packages/sklearn/metrics/_regression.py:492: FutureWarning: 'squared' is deprecated in version 1.4 and will be removed in 1.6. To calculate the root mean squared error, use the function'root_mean_squared_error'. warnings.warn( /opt/anaconda3/lib/python3.12/site-packages/sklearn/metrics/_regression.py:492: FutureWarning: 'squared' is deprecated in version 1.4 and will be removed in 1.6. To calculate the root mean squared error, use the function'root_mean_squared_error'. warnings.warn( /opt/anaconda3/lib/python3.12/site-packages/sklearn/metrics/_regression.py:492: FutureWarning: 'squared' is deprecated in version 1.4 and will be removed in 1.6. To calculate the root mean squared error, use the function'root_mean_squared_error'. warnings.warn( /opt/anaconda3/lib/python3.12/site-packages/sklearn/metrics/_regression.py:492: FutureWarning: 'squared' is deprecated in version 1.4 and will be removed in 1.6. To calculate the root mean squared error, use the function'root_mean_squared_error'. warnings.warn( /opt/anaconda3/lib/python3.12/site-packages/sklearn/metrics/_regression.py:492: FutureWarning: 'squared' is deprecated in version 1.4 and will be removed in 1.6. To calculate the root mean squared error, use the function'root_mean_squared_error'. warnings.warn( /opt/anaconda3/lib/python3.12/site-packages/sklearn/metrics/_regression.py:492: FutureWarning: 'squared' is deprecated in version 1.4 and will be removed in 1.6. To calculate the root mean squared error, use the function'root_mean_squared_error'. warnings.warn( /opt/anaconda3/lib/python3.12/site-packages/sklearn/metrics/_regression.py:492: FutureWarning: 'squared' is deprecated in version 1.4 and will be removed in 1.6. To calculate the root mean squared error, use the function'root_mean_squared_error'. warnings.warn( /opt/anaconda3/lib/python3.12/site-packages/sklearn/metrics/_regression.py:492: FutureWarning: 'squared' is deprecated in version 1.4 and will be removed in 1.6. To calculate the root mean squared error, use the function'root_mean_squared_error'. warnings.warn( /opt/anaconda3/lib/python3.12/site-packages/sklearn/metrics/_regression.py:492: FutureWarning: 'squared' is deprecated in version 1.4 and will be removed in 1.6. To calculate the root mean squared error, use the function'root_mean_squared_error'. warnings.warn( /opt/anaconda3/lib/python3.12/site-packages/sklearn/metrics/_regression.py:492: FutureWarning: 'squared' is deprecated in version 1.4 and will be removed in 1.6. To calculate the root mean squared error, use the function'root_mean_squared_error'. warnings.warn( /opt/anaconda3/lib/python3.12/site-packages/sklearn/metrics/_regression.py:492: FutureWarning: 'squared' is deprecated in version 1.4 and will be removed in 1.6. To calculate the root mean squared error, use the function'root_mean_squared_error'. warnings.warn( /opt/anaconda3/lib/python3.12/site-packages/sklearn/metrics/_regression.py:492: FutureWarning: 'squared' is deprecated in version 1.4 and will be removed in 1.6. To calculate the root mean squared error, use the function'root_mean_squared_error'. warnings.warn( /opt/anaconda3/lib/python3.12/site-packages/sklearn/metrics/_regression.py:492: FutureWarning: 'squared' is deprecated in version 1.4 and will be removed in 1.6. To calculate the root mean squared error, use the function'root_mean_squared_error'. warnings.warn( /opt/anaconda3/lib/python3.12/site-packages/sklearn/metrics/_regression.py:492: FutureWarning: 'squared' is deprecated in version 1.4 and will be removed in 1.6. To calculate the root mean squared error, use the function'root_mean_squared_error'. warnings.warn( /opt/anaconda3/lib/python3.12/site-packages/sklearn/metrics/_regression.py:492: FutureWarning: 'squared' is deprecated in version 1.4 and will be removed in 1.6. To calculate the root mean squared error, use the function'root_mean_squared_error'. warnings.warn( /opt/anaconda3/lib/python3.12/site-packages/sklearn/metrics/_regression.py:492: FutureWarning: 'squared' is deprecated in version 1.4 and will be removed in 1.6. To calculate the root mean squared error, use the function'root_mean_squared_error'. warnings.warn( /opt/anaconda3/lib/python3.12/site-packages/sklearn/metrics/_regression.py:492: FutureWarning: 'squared' is deprecated in version 1.4 and will be removed in 1.6. To calculate the root mean squared error, use the function'root_mean_squared_error'. warnings.warn( /opt/anaconda3/lib/python3.12/site-packages/sklearn/metrics/_regression.py:492: FutureWarning: 'squared' is deprecated in version 1.4 and will be removed in 1.6. To calculate the root mean squared error, use the function'root_mean_squared_error'. warnings.warn( /opt/anaconda3/lib/python3.12/site-packages/sklearn/metrics/_regression.py:492: FutureWarning: 'squared' is deprecated in version 1.4 and will be removed in 1.6. To calculate the root mean squared error, use the function'root_mean_squared_error'. warnings.warn( /opt/anaconda3/lib/python3.12/site-packages/sklearn/metrics/_regression.py:492: FutureWarning: 'squared' is deprecated in version 1.4 and will be removed in 1.6. To calculate the root mean squared error, use the function'root_mean_squared_error'. warnings.warn( /opt/anaconda3/lib/python3.12/site-packages/sklearn/metrics/_regression.py:492: FutureWarning: 'squared' is deprecated in version 1.4 and will be removed in 1.6. To calculate the root mean squared error, use the function'root_mean_squared_error'. warnings.warn( /opt/anaconda3/lib/python3.12/site-packages/sklearn/metrics/_regression.py:492: FutureWarning: 'squared' is deprecated in version 1.4 and will be removed in 1.6. To calculate the root mean squared error, use the function'root_mean_squared_error'. warnings.warn( /opt/anaconda3/lib/python3.12/site-packages/sklearn/metrics/_regression.py:492: FutureWarning: 'squared' is deprecated in version 1.4 and will be removed in 1.6. To calculate the root mean squared error, use the function'root_mean_squared_error'. warnings.warn( /opt/anaconda3/lib/python3.12/site-packages/sklearn/metrics/_regression.py:492: FutureWarning: 'squared' is deprecated in version 1.4 and will be removed in 1.6. To calculate the root mean squared error, use the function'root_mean_squared_error'. warnings.warn( /opt/anaconda3/lib/python3.12/site-packages/sklearn/metrics/_regression.py:492: FutureWarning: 'squared' is deprecated in version 1.4 and will be removed in 1.6. To calculate the root mean squared error, use the function'root_mean_squared_error'. warnings.warn( /opt/anaconda3/lib/python3.12/site-packages/sklearn/metrics/_regression.py:492: FutureWarning: 'squared' is deprecated in version 1.4 and will be removed in 1.6. To calculate the root mean squared error, use the function'root_mean_squared_error'. warnings.warn( /opt/anaconda3/lib/python3.12/site-packages/sklearn/metrics/_regression.py:492: FutureWarning: 'squared' is deprecated in version 1.4 and will be removed in 1.6. To calculate the root mean squared error, use the function'root_mean_squared_error'. warnings.warn( /opt/anaconda3/lib/python3.12/site-packages/sklearn/metrics/_regression.py:492: FutureWarning: 'squared' is deprecated in version 1.4 and will be removed in 1.6. To calculate the root mean squared error, use the function'root_mean_squared_error'. warnings.warn( /opt/anaconda3/lib/python3.12/site-packages/sklearn/metrics/_regression.py:492: FutureWarning: 'squared' is deprecated in version 1.4 and will be removed in 1.6. To calculate the root mean squared error, use the function'root_mean_squared_error'. warnings.warn( /opt/anaconda3/lib/python3.12/site-packages/sklearn/metrics/_regression.py:492: FutureWarning: 'squared' is deprecated in version 1.4 and will be removed in 1.6. To calculate the root mean squared error, use the function'root_mean_squared_error'. warnings.warn( /opt/anaconda3/lib/python3.12/site-packages/sklearn/metrics/_regression.py:492: FutureWarning: 'squared' is deprecated in version 1.4 and will be removed in 1.6. To calculate the root mean squared error, use the function'root_mean_squared_error'. warnings.warn( /opt/anaconda3/lib/python3.12/site-packages/sklearn/metrics/_regression.py:492: FutureWarning: 'squared' is deprecated in version 1.4 and will be removed in 1.6. To calculate the root mean squared error, use the function'root_mean_squared_error'. warnings.warn( /opt/anaconda3/lib/python3.12/site-packages/sklearn/metrics/_regression.py:492: FutureWarning: 'squared' is deprecated in version 1.4 and will be removed in 1.6. To calculate the root mean squared error, use the function'root_mean_squared_error'. warnings.warn( /opt/anaconda3/lib/python3.12/site-packages/sklearn/metrics/_regression.py:492: FutureWarning: 'squared' is deprecated in version 1.4 and will be removed in 1.6. To calculate the root mean squared error, use the function'root_mean_squared_error'. warnings.warn( /opt/anaconda3/lib/python3.12/site-packages/sklearn/metrics/_regression.py:492: FutureWarning: 'squared' is deprecated in version 1.4 and will be removed in 1.6. To calculate the root mean squared error, use the function'root_mean_squared_error'. warnings.warn( /opt/anaconda3/lib/python3.12/site-packages/sklearn/metrics/_regression.py:492: FutureWarning: 'squared' is deprecated in version 1.4 and will be removed in 1.6. To calculate the root mean squared error, use the function'root_mean_squared_error'. warnings.warn( /opt/anaconda3/lib/python3.12/site-packages/sklearn/metrics/_regression.py:492: FutureWarning: 'squared' is deprecated in version 1.4 and will be removed in 1.6. To calculate the root mean squared error, use the function'root_mean_squared_error'. warnings.warn( /opt/anaconda3/lib/python3.12/site-packages/sklearn/metrics/_regression.py:492: FutureWarning: 'squared' is deprecated in version 1.4 and will be removed in 1.6. To calculate the root mean squared error, use the function'root_mean_squared_error'. warnings.warn( /opt/anaconda3/lib/python3.12/site-packages/sklearn/metrics/_regression.py:492: FutureWarning: 'squared' is deprecated in version 1.4 and will be removed in 1.6. To calculate the root mean squared error, use the function'root_mean_squared_error'. warnings.warn( /opt/anaconda3/lib/python3.12/site-packages/sklearn/metrics/_regression.py:492: FutureWarning: 'squared' is deprecated in version 1.4 and will be removed in 1.6. To calculate the root mean squared error, use the function'root_mean_squared_error'. warnings.warn( /opt/anaconda3/lib/python3.12/site-packages/sklearn/metrics/_regression.py:492: FutureWarning: 'squared' is deprecated in version 1.4 and will be removed in 1.6. To calculate the root mean squared error, use the function'root_mean_squared_error'. warnings.warn( /opt/anaconda3/lib/python3.12/site-packages/sklearn/metrics/_regression.py:492: FutureWarning: 'squared' is deprecated in version 1.4 and will be removed in 1.6. To calculate the root mean squared error, use the function'root_mean_squared_error'. warnings.warn( /opt/anaconda3/lib/python3.12/site-packages/sklearn/metrics/_regression.py:492: FutureWarning: 'squared' is deprecated in version 1.4 and will be removed in 1.6. To calculate the root mean squared error, use the function'root_mean_squared_error'. warnings.warn( /opt/anaconda3/lib/python3.12/site-packages/sklearn/metrics/_regression.py:492: FutureWarning: 'squared' is deprecated in version 1.4 and will be removed in 1.6. To calculate the root mean squared error, use the function'root_mean_squared_error'. warnings.warn( /opt/anaconda3/lib/python3.12/site-packages/sklearn/metrics/_regression.py:492: FutureWarning: 'squared' is deprecated in version 1.4 and will be removed in 1.6. To calculate the root mean squared error, use the function'root_mean_squared_error'. warnings.warn( /opt/anaconda3/lib/python3.12/site-packages/sklearn/metrics/_regression.py:492: FutureWarning: 'squared' is deprecated in version 1.4 and will be removed in 1.6. To calculate the root mean squared error, use the function'root_mean_squared_error'. warnings.warn( /opt/anaconda3/lib/python3.12/site-packages/sklearn/metrics/_regression.py:492: FutureWarning: 'squared' is deprecated in version 1.4 and will be removed in 1.6. To calculate the root mean squared error, use the function'root_mean_squared_error'. warnings.warn( /opt/anaconda3/lib/python3.12/site-packages/sklearn/metrics/_regression.py:492: FutureWarning: 'squared' is deprecated in version 1.4 and will be removed in 1.6. To calculate the root mean squared error, use the function'root_mean_squared_error'. warnings.warn( /opt/anaconda3/lib/python3.12/site-packages/sklearn/metrics/_regression.py:492: FutureWarning: 'squared' is deprecated in version 1.4 and will be removed in 1.6. To calculate the root mean squared error, use the function'root_mean_squared_error'. warnings.warn( /opt/anaconda3/lib/python3.12/site-packages/sklearn/metrics/_regression.py:492: FutureWarning: 'squared' is deprecated in version 1.4 and will be removed in 1.6. To calculate the root mean squared error, use the function'root_mean_squared_error'. warnings.warn( /opt/anaconda3/lib/python3.12/site-packages/sklearn/metrics/_regression.py:492: FutureWarning: 'squared' is deprecated in version 1.4 and will be removed in 1.6. To calculate the root mean squared error, use the function'root_mean_squared_error'. warnings.warn( /opt/anaconda3/lib/python3.12/site-packages/sklearn/metrics/_regression.py:492: FutureWarning: 'squared' is deprecated in version 1.4 and will be removed in 1.6. To calculate the root mean squared error, use the function'root_mean_squared_error'. warnings.warn( /opt/anaconda3/lib/python3.12/site-packages/sklearn/metrics/_regression.py:492: FutureWarning: 'squared' is deprecated in version 1.4 and will be removed in 1.6. To calculate the root mean squared error, use the function'root_mean_squared_error'. warnings.warn( /opt/anaconda3/lib/python3.12/site-packages/sklearn/metrics/_regression.py:492: FutureWarning: 'squared' is deprecated in version 1.4 and will be removed in 1.6. To calculate the root mean squared error, use the function'root_mean_squared_error'. warnings.warn( /opt/anaconda3/lib/python3.12/site-packages/sklearn/metrics/_regression.py:492: FutureWarning: 'squared' is deprecated in version 1.4 and will be removed in 1.6. To calculate the root mean squared error, use the function'root_mean_squared_error'. warnings.warn( /opt/anaconda3/lib/python3.12/site-packages/sklearn/metrics/_regression.py:492: FutureWarning: 'squared' is deprecated in version 1.4 and will be removed in 1.6. To calculate the root mean squared error, use the function'root_mean_squared_error'. warnings.warn( /opt/anaconda3/lib/python3.12/site-packages/sklearn/metrics/_regression.py:492: FutureWarning: 'squared' is deprecated in version 1.4 and will be removed in 1.6. To calculate the root mean squared error, use the function'root_mean_squared_error'. warnings.warn( /opt/anaconda3/lib/python3.12/site-packages/sklearn/metrics/_regression.py:492: FutureWarning: 'squared' is deprecated in version 1.4 and will be removed in 1.6. To calculate the root mean squared error, use the function'root_mean_squared_error'. warnings.warn(
✅ Hybrid α-ratio: R² = 0.9767, RMSE = 2.24, Pearson r = 0.9884
/opt/anaconda3/lib/python3.12/site-packages/sklearn/metrics/_regression.py:492: FutureWarning: 'squared' is deprecated in version 1.4 and will be removed in 1.6. To calculate the root mean squared error, use the function'root_mean_squared_error'. warnings.warn( /opt/anaconda3/lib/python3.12/site-packages/sklearn/metrics/_regression.py:492: FutureWarning: 'squared' is deprecated in version 1.4 and will be removed in 1.6. To calculate the root mean squared error, use the function'root_mean_squared_error'. warnings.warn( /opt/anaconda3/lib/python3.12/site-packages/sklearn/metrics/_regression.py:492: FutureWarning: 'squared' is deprecated in version 1.4 and will be removed in 1.6. To calculate the root mean squared error, use the function'root_mean_squared_error'. warnings.warn( /opt/anaconda3/lib/python3.12/site-packages/sklearn/metrics/_regression.py:492: FutureWarning: 'squared' is deprecated in version 1.4 and will be removed in 1.6. To calculate the root mean squared error, use the function'root_mean_squared_error'. warnings.warn( /opt/anaconda3/lib/python3.12/site-packages/sklearn/metrics/_regression.py:492: FutureWarning: 'squared' is deprecated in version 1.4 and will be removed in 1.6. To calculate the root mean squared error, use the function'root_mean_squared_error'. warnings.warn(
